The composition of a group determines much of its behavior (are people old or young, PhDs or illiterate, artists or scientists?). As a result, organizations, governments, and companies are deeply interested in being able to quickly learn the makeup of groups. In order to approach this problem, we’ve been developing technologies for inferring the demographics of Twitter populations from unstructured, textual content that the users in them produce. Our methods stand out as the most accurate in the literature. In this talk, I’m going to give an overview of the latent attribute inference problem, discuss the advances that we’ve made in solving it, and highlight some of the big issues that still need to be tackled.